The hippocampus mediates the formation of adaptive memory for positive or negative experiences, but the neurophysiological mechanisms of this learning process remain unknown. The hippocampus may encode locations independently from the stimuli and events that are associated with these locations.
A human neck replica was made to simulate dynamic response to axial loading, H1. Dynamic loading of neck replica can simulate realistic axial-compression injury to the cervical spine. H2. Severity of measured neck force depends upon impact load and velocity. H3. Neck flexion-extension position affects measured neck force. H4. Simulated neck musculature affects neck stability.
The gut microbiome varies greatly between individuals, and this variation could have important health consequences. These differences may be due to deterministic differences such as genetic differences between individuals or differences in individual history and environmental exposure; stochasticity may also play a role in variation between individual communities.
Computational protein design tools to date have been useful for engineering proteins with a wide range of functions, including DNA binding, co-factor binding, catalysis, fluorescence spectral change, peptide-protein specificity, and protein-protein interaction. In building nanostructures, computational protein design methods have been applied to designing hyperthermophilic proteins, metalloproteins, water-soluble membrane channels, and higher order macromolecular assemblies. Many of these successes rely on fixed backbone approaches that maintain the backbone conformations seen in the original high-resolution crystal structures and focus on remodeling only the sidechains.
Metabolic engineering of microbial strains has been of great interest for producing a wide variety of chemicals including biofuels, polymer precursors, and drugs. While conventional metabolic engineering approaches often focus on modifications to the desired and neighboring pathways, recent developments in computational analysis of metabolic models allow identification of genetic modifications needed to improve production of biochemicals
When making decisions in a group, individuals can adapt their initial beliefs according to the social influence produced by the opinions of other individuals in the group. In modern society, this type of process is widespread and can be seen in settings ranging from work meetings to the courtroom.
The outcome of infection by the human immunodeficiency virus-1 (HIV-1, henceforth “HIV” for simplicity) is highly variable across individuals, with time to AIDS ranging from 2 years to more than 20 years [1–4]. Quantifying the fraction of this variability explained by genetic variability in the virus is important to our understanding of the mechanisms of pathogenesis and of the evolution of virulence [5].
The brain has limited processing capacity, yet it is constantly confronted with enormous amounts of information. Attentional mechanisms are therefore needed to selectively enhance the most task-relevant information.
Should I rather bring the groceries from the car trunk to the kitchen in 1 trip or in 2 trips? Even in a seemingly simple decision like this, multiple decision parameters are at odds. When doing a single trip, this bothersome task will certainly be finished more quickly but will require an intense physical effort
Group sizes in preclinical research are seldom informed by statistical power considerations but rather are chosen on practicability [1, 2]. Typical sample sizes are small, around n = 8 per group (http://www.dcn.ed.ac.uk/camarades/), and are only sufficient to detect relatively large sizes of effects. Consequently, true positives are often missed (false negatives), and many statistically significant findings are due to chance (false positives).
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